Development of a Reinforcement Learning Algorithm to Optimize Corticosteroid Therapy in Critically Ill Patients with Sepsis

Background: The optimal indication, dose, and timing of corticosteroids in sepsis is controversial. Here, we used reinforcement learning to derive the optimal steroid policy in septic patients based on data on 3051 ICU admissions from the AmsterdamUMCdb intensive care database. Methods: We identifie...

Descripción completa

Detalles Bibliográficos
Autores principales: Bologheanu, Razvan, Kapral, Lorenz, Laxar, Daniel, Maleczek, Mathias, Dibiasi, Christoph, Zeiner, Sebastian, Agibetov, Asan, Ercole, Ari, Thoral, Patrick, Elbers, Paul, Heitzinger, Clemens, Kimberger, Oliver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961939/
https://www.ncbi.nlm.nih.gov/pubmed/36836046
http://dx.doi.org/10.3390/jcm12041513

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961939/
https://www.ncbi.nlm.nih.gov/pubmed/36836046
http://dx.doi.org/10.3390/jcm12041513

Ejemplares similares